Download Section 5.2

Normal Distributions: Finding Probabilities
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Section 5.2 Objectives

Find probabilities for normally distributed
variables
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Probability and Normal
Distributions

If a random variable x is normally distributed,
you can find the probability that x will fall in a
given interval by calculating the area under
the normal curve for that interval.
μ = 500
σ = 100
P(x < 600) = Area
x
μ =500 600
Larson/Farber 4th ed
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Probability and Normal
Distributions
Normal Distribution
Standard Normal Distribution
μ = 500 σ = 100
μ=0 σ=1
P(x < 600)
x   600  500
z

1

100
P(z < 1)
z
x
μ =500 600
μ=0 1
Same
Area
P(x < 500) = P(z < 1)
Larson/Farber 4th ed
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Example: Finding Probabilities
for Normal Distributions
A survey indicates that people use their computers
an average of 2.4 years before upgrading to a new
machine. The standard deviation is 0.5 year. A
computer owner is selected at random. Find the
probability that he or she will use it for fewer than 2
years before upgrading. Assume that the variable x
is normally distributed.
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Solution: Finding Probabilities for
Normal Distributions
Normal Distribution
μ = 2.4 σ = 0.5
Standard Normal Distribution
μ=0 σ=1
x   2  2.4
z

 0.80

0.5
P(x < 2)
P(z < -0.80)
0.2119
z
x
2 2.4
-0.80 0
P(x < 2) = P(z < -0.80) = 0.2119
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Example: Finding Probabilities
for Normal Distributions
A survey indicates that for each trip to the
supermarket, a shopper spends an average of 45
minutes with a standard deviation of 12 minutes in
the store. The length of time spent in the store is
normally distributed and is represented by the
variable x. A shopper enters the store. Find the
probability that the shopper will be in the store for
between 24 and 54 minutes.
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Solution: Finding Probabilities for
Normal Distributions
Normal Distribution
μ = 45 σ = 12
x-
Standard Normal Distribution
μ=0 σ=1
24 - 45
 -1.75

12
x -  54 - 45
z2 

 0.75

12
z1 
P(24 < x < 54)

P(-1.75 < z < 0.75)
0.7734
0.0401
x
24
45 54
z
-1.75
0 0.75
P(24 < x < 54) = P(-1.75 < z < 0.75)
= 0.7734 – 0.0401 = 0.7333
Larson/Farber 4th ed
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Example: Finding Probabilities
for Normal Distributions
Find the probability that the shopper will be in the store
more than 39 minutes. (Recall μ = 45 minutes and
σ = 12 minutes)
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Solution: Finding Probabilities for
Normal Distributions
Normal Distribution
μ = 45 σ = 12
z
P(x > 39)
Standard Normal Distribution
μ=0 σ=1
x-


39 - 45
 -0.50
12
P(z > -0.50)
0.3085
z
x
39 45
-0.50 0
P(x > 39) = P(z > -0.50) = 1– 0.3085 = 0.6915
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Example: Finding Probabilities
for Normal Distributions
If 200 shoppers enter the store, how many
shoppers would you expect to be in the store
more than 39 minutes?
Solution:
Recall P(x > 39) = 0.6915
200(0.6915) =138.3 (or about 138) shoppers
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Example: Using Technology to
find Normal Probabilities
Assume that cholesterol levels of men in the United States are normally
distributed, with a mean of 215 milligrams per deciliter and a standard
deviation of 25 milligrams per deciliter. You randomly select a man from the
United States. What is the probability that his cholesterol level is less than
175? Use a technology tool to find the probability.
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Solution: Using Technology to
find Normal Probabilities
Must specify the mean, standard deviation, and
the x-value(s) that determine the interval.
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Section 5.2 Summary

Found probabilities for normally
distributed variables
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